We view Digital Ecosystems to be the digital counterparts of biological ecosystems, exploiting the self-organising properties of biological ecosystems, which are considered to be robust, self-organising and scalable architectures that can automatically solve complex, dynamic problems. Digital Ecosystems are a novel optimisation technique where the optimisation works at two levels: a first optimisation, migration of agents (representing services) which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. We created an Ecosystem-Oriented Architecture of Digital Ecosystems by extending Service-Oriented Architectures with distributed evolutionary computing, allowing services to recombine and evolve over time, constantly seeking to improve their effectiveness for the user base. Individuals within our Digital Ecosystem will be applications (groups of services), created in response to user requests by using evolutionary optimisation to aggregate the services. These individuals will migrate through the Digital Ecosystem and adapt to find niches where they are useful in fulfilling other user requests for applications. Simulation results imply that the Digital Ecosystem performs better at large scales than a comparable Service-Oriented Architecture, suggesting that incorporating ideas from theoretical ecology can contribute to useful self-organising properties in digital ecosystems.
Is mimicking ecosystems the future of information systems? A key challenge in modern computing is to develop systems that address complex, dynamic problems in a scalable and efficient way, because the increasing complexity of software makes designing and maintaining efficient and flexible systems a growing challenge [2], [3], [4]. What with the ever expanding number of services being offered online from Application Programming Interfaces (APIs) being made public, there is an ever growing number of computational units available to be combined in the creation of applications. However, this is currently a task done manually by programmers, and it has been argued that current software development techniques have hit a complexity wall [5], which can only be overcome by automating the search for new algorithms. There are several existing efforts aimed at achieving this automated service composition [6], [7], [8], [9], the most prevalent of which is Service-Oriented Architectures and its associated standards and technologies [10], [11].
Alternatively, nature has been in the research business for 3.8 billion years and in that time has accumulated close to This work is supported by the European Commission under the EU project Digital Business Ecosystems (contract number 507953 [1]). 30 million well-adjusted solutions to a plethora of design challenges that humankind struggles to address with mixed results [12]. Biomimicry is a discipline that seeks solutions by emulating nature’s designs and processes, and there is considerable opportunity to learn elegant solutions for human-made problems [12]. Biological ecosystems are thought to be robust, scalable architectures that can automatically solve complex, dynamic problems, possessing several properties that may be useful in automated systems. These properties include self-organisation, self-management, scalability, the ability to provide complex solutions, and automated composition of these complex solutions [13].
Therefore, an approach to the aforementioned challenge would be to develop Digital Ecosystems, artificial systems that aim to harness the dynamics that underlie the complex and diverse adaptations of living organisms in biological ecosystems. While evolution may be well understood in computer science under the auspices of evolutionary computing [14], ecological models are not. The possible connections between Digital Ecosystems and their biological counterparts are yet to be closely examined, so potential exists to create an Ecosystem-Oriented Architecture with the essential elements of biological ecosystems, where the word ecosystem is more than just a metaphor. We propose that an ecosystem inspired approach, would be more effective at greater scales than traditionally inspired approaches, because it would be built upon the scalable and self-organising properties of biological ecosystems [13].
Our approach to evolving high-level software applications requires a modular reusable paradigm to software development. Service-oriented architectures (SOAs) are the current state-of-the-art approach, being the current iteration of interface/component-based design from the 1990s, which was itself an iteration of event-oriented design from the 1980s, and before then modular programming from the 1970s [15], [16]. Service-oriented computing promotes assembling application components into a loosely coupled network of services, to create flexible, dynamic business processes and agile applications that span organisations and computing platforms [17]. This is achieved through a SOA, an architectural style that guides all aspects of creating and using business processes throughout their life-cycle, packaged as services. This includes defining and provisioning the infrastructure that allows different applications to exchange data and participate in business processes, loosely coupled from the operating systems and programming languages underlying the applications [18]. Hence, a SOA represents a model in which functionality is decomposed into distinct units (services), which can be distributed over a network, and can be combined and reused to create business applications [17].
A SOA depends upon service-orientation as its fundamental design principle. In a SOA environment, independent services can be accessed without knowledge of their underlying platform implementation [18]. Services reflect a service-oriented approach to programming that is based on composing applications by discovering and invoking networkavailable services to accomplish some task. This approach is independent of specific programming languages or operating systems, because the services communicate with each other by passing data from one service to another, or by coordinating an activity between two or more services [17]. So, the concepts of SOAs are often seen as built upon, and the development of, the concepts of modular programming and distributed computing [16].
SOAs allow for an information system a
This content is AI-processed based on open access ArXiv data.
